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Global water governance and water rights through the prism of Canaan, a slum apart in Haiti

2021· article· en· W3194736787 on OpenAlexfundno aff
Évens Emmanuel, Yolette Jérôme, Pascal Saffache

Bibliographic record

VenueAQUA-LAC · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicWater Governance and Infrastructure
Canadian institutionsnot available
FundersAgence Universitaire de la Francophonie
KeywordsSlumSanitationHuman settlementGroundwater rechargeEnvironmental planningHuman rightsWater resourcesCorporate governanceGeographyPolitical scienceWater resource managementBusinessGroundwaterAquiferSociologyLawEnvironmental scienceEngineeringPopulationEnvironmental engineeringEcologyArchaeology

Abstract

fetched live from OpenAlex

In Haitian cities, the disorganization of urban planning most often leads to the creation of new human settlements, which lack basic services, such as the provision of drinking water and sanitation. The proliferation of slums has an unfavorable effect on the hydrological cycle by reducing the permeabilized surfaces, causing significant disturbances in the recharge of groundwater. Furthermore, the impact of global changes on cities today is causing water scarcity, which makes it difficult to manage water resources effectively. Taken in the prism of environmental conditions and the way in which the metropolitan area of Port-au-Prince is to be developed, this situation not only deprives the populations of the slums of this vital element, but also violates one of their fundamental rights "the right to water and sanitation". Canaan, a human establishment created following the earthquake of January 12, 2010 by presidential decree, and inhabited by the victims of this event, constitutes in itself a real field laboratory allowing the veracity of such an assertion to be tested. The objective of this work is to analyze in the light of the major trends in global water governance, the right to water, one of the fundamental human rights, in Canaan.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.768
Threshold uncertainty score0.908

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.009
GPT teacher head0.247
Teacher spread0.238 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2021
Admission routes1
Has abstractyes

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